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Compositing Graphs IQR Outlier Flags + Date by Category Pivot
x402
Compositing Graphs IQR Outlier Flags + Date by Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-17).
Runs two analytical reports on compositing graph records — IQR-based outlier flagging and a date-by-category pivot — for up to 200 supplied rows of node_count and render_seconds data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Compositing graphs — IQR outlier flags + Date by category pivot: IQR outlier flags + Date by category pivot for supplied compositing graphs records (node_count, render_seconds). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Returns two independent analytical reports: (1) IQR outlier flags identifying which rows have statistically anomalous values for the selected field (node_count or render_seconds), and (2) a date-by-category pivot table summarizing the selected metric across asset_group and date dimensions. All computation is performed locally on the supplied data with no external lookups.
Example use cases
Detecting render time anomalies in VFX pipeline
“I have 120 compositing job records with node_count and render_seconds across asset groups like 'hero-comp' and 'bg-layer' from 2025-03-01 to 2025-06-30 — can you flag any IQR outliers and pivot render_seconds by asset group and date?”
Auditing node count spikes across asset groups
“Here are 80 compositing graph rows spanning asset groups 'fx-pass' and 'lighting-comp' between 2024-11-01 and 2025-01-31 — run IQR outlier flagging on node_count and show me a date-by-category breakdown so I can see where counts spike.”
Post-production performance review for compositing team
“We finished a production run with 150 compositing records across groups 'matte-paint', 'cg-comp', and 'grade-pass' from 2025-04-01 to 2025-04-30 — can you detect render_seconds outliers using IQR and pivot the data by asset group and date for our performance review?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-creative-09-178?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both IQR-based outlier detection and a date-by-category pivot in a single call on compositing graph data (node_count, render_seconds), without requiring external data sources, model inference, or live lookups. It is well-suited for post-production analytics, pipeline auditing, and performance diagnostics on batches of up to 200 compositing job records.
Side effects
- Missing required fields (row_id, asset_group, date, node_count, render_seconds) causes validation error
- Date values not matching YYYY-MM-DD pattern are rejected
- Submitting more than 200 rows exceeds the row limit
- Empty rows array returns an error
- Null values for both node_count and render_seconds across all rows may yield empty outlier results
- Invalid field enum value (not 'node_count' or 'render_seconds') causes rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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